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Algorithmic Information Theory and Undecidability
Synthese, 2000Chaitin has proven that the halting probability \(\Omega=\sum\{2^{-|p|}\mid p\text{\;halts}\}\) of a universal Turing machine is not computable, and, moreover, that any recursively axiomatizable theory enables us to determine only finitely many digits of \(\Omega\).
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A statistical mechanical interpretation of algorithmic information theory
SpringerBriefs in Mathematical Physics, 2008We develop a statistical mechanical interpretation of algorithmic information theory by introducing the notion of thermodynamic quantities, such as free energy, energy, statistical mechanical entropy, and specific heat, into algorithmic information ...
K. Tadaki
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Project: algorithmic-informational system theory
2020Notes, emails, sketches and working papers for the respective research.
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A consistency algorithm based on information theory
Mathematical Population Studies, 1994"This paper provides a geometric-mean solution to the consistency problem of multidimensional demographic projection models, based on the constrained minimization of an entropy function. A comparison with the existing harmonic-mean solution yields many similarities and almost no differences....However, one major advantage of the geometric mean is that
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Information Theory, Inference, and Learning Algorithms
Journal of the American Statistical Association, 2005(2005). Information Theory, Inference, and Learning Algorithms. Journal of the American Statistical Association: Vol. 100, No. 472, pp. 1461-1462.
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Analytic algorithmics, combinatorics, and information theory
IEEE Information Theory Workshop, 2005., 2005Analytic information theory aims at studying problems of information theory using analytic techniques of computer science and combinatorics. Following Hadamard's and Knuth's precept, we tackle these problems by complex analysis methods such as generating functions, Mellin transform, Fourier series, saddle point method, analytic poissonization and de ...
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Algorithmic Information Theory and Computational Complexity
2013We present examples where theorems on complexity of computation are proved using methods in algorithmic information theory. The first example is a non-effective construction of a language for which the size of any deterministic finite automaton exceeds the size of a probabilistic finite automaton with a bounded error exponentially.
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Information, Randomness and Incompleteness - Papers on Algorithmic Information Theory; 2nd Edition
World Scientific Series in Computer Science, 1987G. Chaitin
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009
Andrew R. Cohen +4 more
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Andrew R. Cohen +4 more
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Algorithmic Information Theory-Based Analysis of Earth Observation Images: An Assessment
IEEE Geoscience and Remote Sensing Letters, 2010D. Cerra +3 more
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